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We are looking for a skilled Malware Reverse Engineer to join our group. In this role, you'll analyze emerging cyber threats, dissect sophisticated malware families, and transform your technical findings into actionable insights.

In this role, you will architect and implement large-scale distributed systems, low-level platform components, and high-performance services that underpin core product stack. You will drive technical strategy across system reliability, performance, and scalability, partnering closely with product, infrastructure, and data engineering teams to deliver systems that operate at global scale with high availability and efficiency.
Software Engineer, Systems Responsibilities
Architect and implement large-scale distributed systems and platform services that support high-throughput, low-latency workloads across Meta's product infrastructure
Lead the technical design of systems components including storage layers, compute pipelines, networking abstractions, and service orchestration frameworks
Identify and resolve systemic performance bottlenecks through instrumentation, profiling, and targeted optimization across the full systems stack
Define and enforce service level objectives for owned systems, building dashboards, alerting pipelines, and runbooks to reduce mean time to mitigation during incidents
Drive reliability improvements by reducing failure surface, designing resilient rollout strategies, and leading regular resiliency and overload testing exercises
Collaborate with cross-functional partners across product engineering, infrastructure, and data science to align system architecture with evolving product and business requirements
Establish and evolve coding standards, architectural patterns, and engineering best practices for systems development across the broader organization
Leverage AI-assisted development workflows to accelerate design iteration, code generation, and systems analysis, applying sound judgment on when to rely on AI versus deep systems expertise
Mentor other engineers on systems design principles, debugging methodologies, and production operations, and contribute to onboarding programs for new team members
Lead incident retrospectives, identify root causes of complex production failures, and drive implementation of systemic improvements to prevent recurrence

In this role, you will operate as a company-level expert in product analytics, partnering with Product, Engineering, and cross-functional leadership to translate complex, large-scale behavioral data into actionable insights that shape the experiences of billions of people worldwide. You will lead the design of rigorous analytical frameworks, advance forecasting and predictive modeling capabilities, and influence the highest-priority product investments through data-driven storytelling and strategic recommendations.
Data Scientist, Product Analytics Responsibilities
Lead the design and execution of complex analytical projects across product areas, applying advanced statistical methods, causal inference, and experimentation to evaluate product impact at scale
Develop and maintain sophisticated predictive models and forecasting frameworks to inform product roadmaps, goal setting, and resource prioritization
Define and evolve success metrics and measurement strategies for product initiatives, ensuring goals accurately reflect user and business value
Identify and size high-impact product opportunities by synthesizing behavioral data, qualitative signals, and business context across multiple data sources
Partner with Product and Engineering teams to design and analyze large-scale A/B tests and feature rollouts, translating results into clear recommendations for product direction
Build scalable, self-service data pipelines and visualization interfaces that enable cross-functional teams to explore and act on product performance data independently
Communicate complex analytical findings to diverse audiences including product leadership and executives through concise, compelling data narratives and presentations
Contribute to functional data science strategy by proactively identifying methodological gaps, championing analytical best practices, and setting goals across teams
Mentor other data scientists on analytical design, hypothesis formulation, and quantitative modeling, elevating the overall quality and rigor of the team's work
Collaborate with Data Engineering and Research partners to improve data infrastructure, eliminate bias in data collection, and ensure analytical outputs accurately represent the populations of interest

The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk . The principal will enable the risk organization to deliver significant lift over current long range objectives for friction and leakage through the generation of new Machine Learning opportunities for the organization and support of successful delivery of the risk management ML architecture. This person will partner closely with the FRM engineering leader (Director level) and be part of Metas risk management leadership circle.
Software Engineer, ML (Technical Leadership) Responsibilities
Address core business and technical machine learning opportunities: elevate the existing portfolio of machine learning solutions to be state-of-the-art for minimizing Metas financial losses (due to leakage, good revenues loss and friction). Following are a few examples of technical and business problems we aim to address. - Provide a solution for optimizing the risk machine learning model ensemble (covering the entire end-to-end advertiser funnel including detection, decisioning, enforcement and remediation) through optimization of the current model portfolio and individual models. - Minimize the impact of the prolonged financial fraud feedback loop. - Improve models measurement and performance. - Optimize data/label strategy. - Optimize balance between specific targeted model strategy and broad umbrella model strategy to optimize for short and long term benefits
Lead Research and Introduction of Advanced Technologies: - Collaborate with Financial Integrity's senior ML Engineers to lead the research and introduction of deep learning and Large Language Model (LLM) technologies. - Remain current on industry-wide advancements in ML and introduce relevant advancements in Financial Risk Management
Collaborate on Next-Generation ML Architecture: - Work closely with financial harms principals and risk management tech leads to deliver the next-generation ML architecture for Meta's risk management system. - Collaborate with Principal ML engineers from across the company to adopt best industry and Meta practices within the FRM team. - Resolve or mitigate design dilemmas, balancing business and technical trade-offs. - Identify and initiate opportunities for collaboration and impact with other organizations at Meta
Identify and Initiate New Business Opportunities: - Collaborate with Meta FinTech, Central Integrity and Core Ads Growth partnerships to identify and initiate new business opportunities based on third-party capabilities. - Conduct proof of concept for different opportunities and initiate integrations to enhance business performance
Grow Other Senior ML Engineers - Actively invest in the growth of other senior ML engineers through goal-driven formal and informal mentorship. Provide regular feedback to other engineers regarding their technical work

we are looking for a AI Engineer.
Our R&D teams build and own the features that power platform - from deep code analysis to risk detection to developer-facing workflows. AI isn't a separate initiative here; it's how we build. Every engineering team is actively embedding LLMs, AI agents, and generative AI into the products they own, moving from experimentation to production and keeping things running reliably once they're there.
What You Will Do
Build and ship end-to-end AI-driven features and agentic workflows- from experimentation through validation to production deployment (Python and C#).
Design scalable backend services that support production-grade agentic AI capabilities.
Develop and improve solutions powered by LLMs, AI agents, multi-agent systems, and generative AI frameworks.
Evaluate agentic architectures and model performance, owning monitoring, reliability, and continuous improvement in production.
Collaborate cross-functionally with software engineers, data scientists, and analysts to drive AI innovation across the platform.

we are looking for a Software Engineer.
Our Engineering team builds the platform that powers Apiiro's mission: giving development teams the risk context to ship fast and stay secure. We work across a rich technical stack - from deep code analysis engines to customer-facing features - and take full ownership of what we build, from architecture to production. We move fast, collaborate closely with product and customers, and aren't afraid to tackle hard problems.
What You Will Do:
Build robust, scalable systems using a mix of languages, frameworks, and machine learning models, taking full ownership of features from idea to live product.
Collaborate directly with customers to understand their needs and integrate valuable insights into your work.
Drive cross-disciplinary initiatives across tech domains - from DevOps and infrastructure to data engineering and full-stack development - expanding your impact company-wide.
Partner with product and research teams to deliver innovative security capabilities that make a real difference for development teams.

we are looking for a Manager, Data Science & Research.
What will you do:
Lead development of content classification systems across social platforms (Meta, TikTok, YouTube), web, and apps
Design and build models across computer vision, NLP, and multimodal pipelines
Own the full lifecycle: data selection -> labeling strategy -> training -> evaluation -> deployment
Develop strategies for efficient data curation and labeling (active learning, auto-labeling, sampling under scale)
Improve model quality (precision/recall) while balancing cost, latency, and scale
Drive automation systems (auto-labeling, auto-curation, retraining loops)
Apply modern AI approaches (LLMs, embeddings, foundation models) to real production problems
Lead and mentor a team of senior Data Scientists, setting technical direction and pushing execution forward
Work closely with ML Engineering, Product, and Policy to translate ambiguous requirements into scalable systems

We're looking for a talented DevOps Engineer to join our team. As a DevOps Engineer, you will architect and operate scalable, resilient cloud environments, using advanced automation and AI-based tools to improve system health, reduce manual intervention, and optimize infrastructure costs.
Responsibilities
Own the full lifecycle of the Coin Master platform. Ensure high availability, performance, and cost-efficiency across our multi-region AWS environment.
Design and maintain robust, high-performance infrastructure using IaC. You will focus on building self-healing environments where AI agents continuously monitor and remediate issues in real-time.
Embed security into the infrastructure layer. Leverage AI-assisted tooling to proactively identify and patch vulnerabilities across our Kubernetes clusters and AWS stack.
Build tools and services that empower our engineering team to ship code faster. You are the architect of the platform, ensuring it is intuitive, scalable, and fully automated.

We are looking for an experienced and passionate Game Engineer to take a key role in developing our next-generation games. In this role, you will be deeply involved in shaping the core gameplay experience, building robust client architecture in Unity, and taking end-to-end ownership of features - from smooth client interactions to lightweight, scalable backend development.
Responsibilities
Design, build, and maintain high-performance, reusable, and maintainable game features.
Drive features from initial technical design to production, taking responsibility for both client-side logic and the necessary backend endpoints/services
Optimize and scale both client-side gameplay and backend systems for millions of players, ensuring a high-performance, seamless experience across the entire technical stack.
Implement both client and server logic with robust network protocols, state synchronization, and data persistence that seamlessly scale
Work closely with Product Managers, Game Designers, and Artists to iterate quickly on new mechanics and features.

We are seeking a Software Embedded Development Engineer to design, develop, and optimize mission-critical embedded software for cloud infrastructure. You will join teams focused on networking, machine learning acceleration, and high-performance computing (HPC), impacting millions of AWS services globally.

Cutting-Edge Technology: Work on custom silicon (e.g., Graviton, ML accelerators) and innovative networking solutions at the intersection of hardware and software.

Growth & Innovation: Benefit from AWSs resources, mentorship programs, and opportunities to publish technical content.

As a Technical Account Manager (TAM) in AWS Enterprise Support, you will serve as the primary technical advisor and voice of the customer for a portfolio of fast-growing Israeli startups. You will play a crucial role in fostering their innovative and transformative work across AI/ML, compute (including accelerated and GPU workloads), containers, networking, storage, databases, serverless, security, and more. It's an opportunity to work closely with technical founders and engineering leaders, helping them make the right architectural decisions at each stage of their growth journey.

Key job responsibilities
- Act as the primary technical advisor for your startup customers, building trusted-advisor relationships with CTOs, VP Engineering, and founding teams
- Engage across the full customer organization, from individual engineers through to C-suite, adapting your communication to each audience
- Help accelerate customer growth by crafting strategies that balance startup velocity with Well-Architected best practices across AI/ML, compute, containers, and data infrastructure
- Conduct architecture reviews, operational assessments, and proactive risk identification. Analyze service events and operational patterns to drive continuous improvement in resilience, performance, and cost efficiency
- Drive technical discussions with founding teams on architecture trade-offs, incident response, and risk management as their systems scale
- Uplift customer capabilities by running workshops, enablement sessions, and brown bag sessions tailored to their technical needs
- Champion and advocate for your customers by connecting their feedback to AWS engineering teams, influencing platform evolution, and ensuring rapid resolution of concerns
- Collaborate with Solutions Architects, Business Developers, Professional Services, and Account Managers to deliver coordinated customer value
- Develop and share technical content such as blog posts, reference architectures, and reusable solutions that help startups solve common challenges and reduce time-to-market.

We are looking for an experienced Senior DevOps & Platform Engineer to join our DevOps team and help customers modernize their software delivery platforms, cloud infrastructure, and engineering practices.
This role combines hands-on engineering, software development, platform architecture, and customer-facing consulting. You will work directly with customers to assess their development lifecycle, understand their tooling and processes, and design scalable, secure, and automated solutions that accelerate software delivery and improve developer experience.
Responsibilities:
Design, implement, and maintain cloud-native platforms across AWS, Azure, and Kubernetes environments
Implement and optimize Kubernetes platforms and cloud infrastructure solutions for enterprise customers
Build CI/CD pipelines, GitOps workflows, Infrastructure as Code solutions, and deployment automation
Develop automation, integrations, and platform services using Python, Go, and modern engineering practices
Lead customer discovery sessions, technical assessments, and workshops to understand existing development and operational processes
Interview Development, Operations, Security, and Leadership teams to identify challenges and improvement opportunities
Design target-state architectures, platform roadmaps, and implementation plans
Implement observability, monitoring, logging, and security best practices across customer environments
Deliver technical presentations, workshops, and knowledge-transfer sessions
Contribute reusable automation, documentation, and internal platform assets

We're hiring a hands-on delivery engineer to take Cortex deployments from initial setup through production rollout and keep them running well afterward. You'll own the technical execution of Cortex projects for our customers: standing up the platform, onboarding data sources and endpoints, tuning detections, and building automation playbooks. Once a deployment goes live, you'll also pick up operational issues for it and for other customers.
Responsibilities:
Configure and deploy Cortex XDR, XSIAM, and XSOAR, translating architecture and design decisions into a working environment
Lead endpoint agent rollout, log source and data onboarding, and integration configuration across a customer's security and IT stack
Tune detection rules and correlation logic to reduce noise and align with each customer's environment and threat profile
Build and maintain XSOAR playbooks that automate response actions and reduce manual triage work
Troubleshoot production issues across the platform: agent health, ingestion failures, integration breakage, playbook errors, and detection gaps
Write clear documentation and runbooks
Escalate to Palo Alto support channels when an issue requires vendor involvement, and manage the case through to resolution
Validate a project's technical scope against the signed SOW before kickoff, and flag gaps or risks early

Palo Alto Networks is looking for a Senior Software Engineer to join our team responsible for the machine identity and access offering, designing and developing services used as part of Palo Alto Networks' SaaS products.
The team designs and develops services that integrate closely with leading cloud vendors like AWS, Azure, GCP, and many other DevOps services and tools, providing managed access to sensitive assets in the organization.
In this role, you will be using advanced AWS micro-services, with Ruby, Golang, Java and Python through the entire SDLC from planning to production.
The team collaborates with security architects, product managers, and other development teams.
Together we produce complex and advanced solutions that meet the highest security and scalability standards.
We are looking for someone energetic and versatile to join our family and help us achieve our goals.
Design and develop new features using container-based architectures
Research new technologies and platforms
Be a member of a highly talented cross-functional development team of developers, architects, and QA engineers, in an agile oriented environment
Participate in continuous and iterative engineering cycles, emphasizing code quality, supportability, scalability, and performance.